docs: def contour(h, axes=None, zoom=None, label_contour=False, **kwargs):
      """
      Draw a matplotlib contour plot from a 2D ROOT histogram.
  
      Parameters
      ----------
  
      h : Hist2D
          A rootpy Hist2D
  
      axes : matplotlib Axes instance, optional (default=None)
          The axes to plot on. If None then use the global current axes.
  
      zoom : float or sequence, optional (default=None)
          The zoom factor along the axes. If a float, zoom is the same for each
          axis. If a sequence, zoom should contain one value for each axis.
          The histogram is zoomed using a cubic spline interpolation to create
          smooth contours.
  
      label_contour : Boolean, optional (default=False)
          If True, labels are printed on the contour lines.
  
      kwargs : additional keyword arguments, optional
          Additional keyword arguments are passed directly to
          matplotlib's contour function.
  
      Returns
      -------
  
      Returns the value from matplotlib's contour function.
  
      """
      if axes is None:
          axes = plt.gca()
      x = np.array(list(h.x()))
      y = np.array(list(h.y()))
      z = np.array(h.z()).T
      if zoom is not None:
          from scipy import ndimage
          if hasattr(zoom, '__iter__'):
              zoom = list(zoom)
              x = ndimage.zoom(x, zoom[0])
              y = ndimage.zoom(y, zoom[1])
          else:
              x = ndimage.zoom(x, zoom)
              y = ndimage.zoom(y, zoom)
          z = ndimage.zoom(z, zoom)
      return_values = axes.contour(x, y, z, **kwargs)
      if label_contour:
          plt.clabel(return_values)
      return return_values